Comparative Performance Analysis of State-of-the-Art Classification Algorithms Applied to Lung Tissue Categorization

In this paper, we compare five common classifier families in their ability to categorize six lung tissue patterns in high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD) and with healthy tissue. The evaluated classifiers are naive Bayes, k-nearest neighbor, J48 decision trees, multilayer perceptron, and support vector machines (SVM). The dataset used contains 843 regions of interest (ROI) of healthy and five pathologic lung tissue patterns identified by two radiologists at the University Hospitals of Geneva. Correlation of the feature space composed of 39 texture attributes is studied. A grid search for optimal parameters is carried out for each classifier family. Two complementary metrics are used to characterize the performances of classification. These are based on McNemar's statistical tests and global accuracy. SVM reached best values for each metric and allowed a mean correct prediction rate of 88.3% with high class-specific precision on testing sets of 423 ROI

Investigating the enabling factors influencing occupational therapists’ adoption of assisted living technology

Introduction Research into technology adoption has focused on older adults’ motivations, with less exploration of the perspective of healthcare providers, including occupational therapists, who are often described as the gatekeepers to assisted living technology. Method This qualitative study utilized semi-structured interviews and focus groups with 20 occupational therapists in England and Scotland. The goal was to identify those enabling factors necessary for occupational therapists to adopt assisted living technology. Results Five themes emerged regarding the enablers needed to support the adoption of assisted living technology by occupational therapists, including: (1) a positive client–therapist relationship; (2) affordability; (3) time; (4) increased awareness, education, and training; and (5) usability features of the assisted living technology. Conclusion With an aging population and the increasing role that technology is playing globally in older adults’ lives, it has never been more important for occupational therapists to harness the potential of new, developing, and existing technologies to support people to live and age as well as possible. To accomplish this, however, requires that occupational therapists are equipped with the time, training, and education necessary to offer their clients assisted living technologies that are client-centered, usable, and affordabl

Advancing Models and Theories for Digital Behavior Change Interventions

To be suitable for informing digital behavior change interventions, theories and models of behavior change need to capture individual variation and changes over time. The aim of this paper is to provide recommendations for development of models and theories that are informed by, and can inform, digital behavior change interventions based on discussions by international experts, including behavioral, computer, and health scientists and engineers. The proposed framework stipulates the use of a state-space representation to define when, where, for whom, and in what state for that person, an intervention will produce a targeted effect. The "state" is that of the individual based on multiple variables that define the "space" when a mechanism of action may produce the effect. A state-space representation can be used to help guide theorizing and identify crossdisciplinary methodologic strategies for improving measurement, experimental design, and analysis that can feasibly match the complexity of real-world behavior change via digital behavior change interventions

The federal government and public morals

Thesis (M.A.)--University of Kansas, History, 1930

The Effect of Music Familiarity on Driving: A Simulated Study of the Impact of Music Familiarity Under Different Driving Conditions

Music is one of the most popular activities while driving. Previous research on music while driving has been mixed, with some researchers finding music to be a distractor and some research finding music to be facilitative to driving performance. The current study was designed to determine if familiarity with the music might explain the difference found between self-selected and experimenter-selected music, and whether the difficulty of the driving conditions affected music’s relationship to driving performance. One hundred and sixty-five University students participated in a driving simulation both with music and without music. Under the “with music” condition, participants were randomly assigned to three music conditions: self-selected music, experimenter-selected familiar music, and experimenter-selected unfamiliar music. In the simulation drive, participants first drove under a simple, low-mental workload condition (car following task in a simulated suburban road) and then drove under a complex, high-mental workload condition (city/urban road). The results showed that whether music was self- or experimenter-selected did not affect driving performance. Whether the music was familiar or unfamiliar did not affect performance either. However, self-selected music appeared to improve driving performance under low-workload conditions, leading to less car-following delay and less standard deviation in steering, but also caused participants to drive faster, leading to faster mean speed and higher car-following modulus, but not more speed limit violations. Self-selected music did not have any significant effect in high-mental workload conditions

Factors that promote or inhibit the implementation of e-health systems: an explanatory systematic review

OBJECTIVE: To systematically review the literature on the implementation of e-health to identify: (i) barriers and facilitators to e-health implementation, and (ii) outstanding gaps in research on the subject.METHODS: MEDLINE, EMBASE, CINAHL, PSYCINFO and the Cochrane Library were searched for reviews published between 1 January 1995 and 17 March 2009. Studies had to be systematic reviews, narrative reviews, qualitative metasyntheses or meta-ethnographies of e-health implementation. Abstracts and papers were double screened and data were extracted on country of origin; e-health domain; publication date; aims and methods; databases searched; inclusion and exclusion criteria and number of papers included. Data were analysed qualitatively using normalization process theory as an explanatory coding framework.FINDINGS: Inclusion criteria were met by 37 papers; 20 had been published between 1995 and 2007 and 17 between 2008 and 2009. Methodological quality was poor: 19 papers did not specify the inclusion and exclusion criteria and 13 did not indicate the precise number of articles screened. The use of normalization process theory as a conceptual framework revealed that relatively little attention was paid to: (i) work directed at making sense of e-health systems, specifying their purposes and benefits, establishing their value to users and planning their implementation; (ii) factors promoting or inhibiting engagement and participation; (iii) effects on roles and responsibilities; (iv) risk management, and (v) ways in which implementation processes might be reconfigured by user-produced knowledge.CONCLUSION: The published literature focused on organizational issues, neglecting the wider social framework that must be considered when introducing new technologies.<br/